0 name 16713 non-null object 3 genre 16713 non-null object
2 year_of_release 16446 non-null float64
9 user_score 10014 non-null object
( name_user_score.map(len).hist(bins=name_user_score.map(len).max()) .set(title='Количество Уникальных Оценок Пользователей для Игр', xlabel='Количество Уникальных Оценок Пользователей', ylabel='Количество Игр') );name_user_score.map(len).max()name_user_score_l1 = restore_column_by_name(name_user_score, 1)name_user_score_l1 = name_user_score_l1.map(lambda x: x[0], na_action='ignore') name_user_score_l1[name_user_score_l1.notna()]user_score_temp = name_user_score_l1[gdf.name] user_score_temp = user_score_temp.reset_index(drop=True) user_score_temp = pd.to_numeric(user_score_temp) user_score_tempgdf.user_score.isna().sum()gdf.user_score.fillna(user_score_temp, inplace = True) gdf.user_score.isna().sum()name_user_score_l2 = restore_column_by_name(name_user_score, 2)
gdf.groupby('name').user_score.agg('median')gdf.groupby('name').user_score.agg('median')[gdf.name].reset_index(drop=True)gdf.user_score = gdf.user_score.astype('Float32')gdf.user_score.isna().sum()gdf.user_score = gdf.user_score.fillna(gdf.groupby('name').user_score.agg('median')[gdf.name].reset_index(drop=True)) gdf.user_score.isna().sum()
8 critic_score 8137 non-null float64
10 rating 9949 non-null object
4 na_sales 16712 non-null float64 5 eu_sales 16712 non-null float64 6 jp_sales 16712 non-null float64 7 other_sales 16712 non-null float64